Jianlin Cheng

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Jie HouSaint Louis UniversityVerified email at slu.edu
Renzhi CaoAssistant Professor at Pacific Lutheran UniversityVerified email at mail.missouri.edu
Pierre BaldiProfessor, University of California, IrvineVerified email at ics.uci.edu
Badri AdhikariUniversity of Missouri-St. LouisVerified email at umsl.edu
Zheng WangAssociate Professor, Department of Computer Science, University of MiamiVerified email at miami.edu
Jesse EickholtCentral Michigan UniversityVerified email at cmich.edu
Jilong LiPillar BiosciencesVerified email at pillar-biosciences.com
Debswapna BhattacharyaAssociate Professor of Computer Science at Virginia TechVerified email at vt.edu
Chen ChenUniversity of Missouri ColumbiaVerified email at mail.missouri.edu
Xin DengMicrosoft CorporationVerified email at microsoft.com
Tianqi WuUniversity of MissouriVerified email at umsystem.edu
James A. BirchlerCurators' Professor of Biological Sciences, University of MissouriVerified email at missouri.edu
Gary StaceyCurator's Professor, Divisions of Plant Science and Biochemistry, C.S. Bond Life Science CenterVerified email at missouri.edu
Zhiye GuoUniveristy of MissouriVerified email at umsystem.edu
Dennis B LubahnProfessor Biochemistry MissouriVerified email at missouri.edu
Oluwatosin OluwadareAssistant Professor, University of Colorado, Colorado SpringsVerified email at uccs.edu
Dong XuCurators’ Distinguished Professor, University of MissouriVerified email at missouri.edu
Michael J SweredoskiMolecular Genetics Pathology Laboratory at KPVerified email at kp.org
Tuan TrieuWeill Cornell MedicineVerified email at med.cornell.edu
Grace SunProfessor of Biochemistry, University of MissouriVerified email at missouri.edu

Jianlin Cheng

William and Nancy Thompson Professor, University of Missouri

Verified email at missouri.edu - Homepage

Bioinformatics Machine Learning Deep Learning Artificial Intelligence


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Genome sequence of the palaeopolyploid soybean J Schmutz, SB Cannon, J Schlueter, J Ma, T Mitros, W Nelson, DL Hyten, ... Nature 463 (7278), 178-183, 2010	4313	2010
SCRATCH: a protein structure and structural feature prediction server J Cheng, AZ Randall, MJ Sweredoski, P Baldi Nucleic acids research 33 (suppl_2), W72-W76, 2005	1086	2005
A large-scale evaluation of computational protein function prediction P Radivojac, WT Clark, TR Oron, AM Schnoes, T Wittkop, A Sokolov, ... Nature methods 10 (3), 221-227, 2013	935	2013
Prediction of protein stability changes for single‐site mutations using support vector machines J Cheng, A Randall, P Baldi Proteins: Structure, Function, and Bioinformatics 62 (4), 1125-1132, 2006	915	2006
An expanded evaluation of protein function prediction methods shows an improvement in accuracy Y Jiang, TR Oron, WT Clark, AR Bankapur, D D’Andrea, R Lepore, ... Genome biology 17 (1), 1-19, 2016	361	2016
A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction M Spencer, J Eickholt, J Cheng IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1, 2014	336	2014
3Drefine: an interactive web server for efficient protein structure refinement D Bhattacharya, J Nowotny, R Cao, J Cheng Nucleic acids research 44 (W1), W406-W409, 2016	328	2016
Improved residue contact prediction using support vector machines and a large feature set J Cheng, P Baldi BMC bioinformatics 8 (1), 113, 2007	302	2007
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens N Zhou, Y Jiang, TR Bergquist, AJ Lee, BZ Kacsoh, AW Crocker, ... Genome biology 20 (1), 1-23, 2019	261	2019
A machine learning information retrieval approach to protein fold recognition J Cheng, P Baldi Bioinformatics 22 (12), 1456-1463, 2006	257	2006
Accurate prediction of protein disordered regions by mining protein structure data J Cheng, MJ Sweredoski, P Baldi Data Mining and Knowledge Discovery 11 (3), 213-222, 2005	256	2005
A neural network approach to ordinal regression J Cheng, Z Wang, G Pollastri 2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008	225	2008
3Drefine: Consistent protein structure refinement by optimizing hydrogen bonding network and atomic‐level energy minimization D Bhattacharya, J Cheng Proteins: Structure, Function, and Bioinformatics, 2012	204	2012
NNcon: improved protein contact map prediction using 2D-recursive neural networks AN Tegge, Z Wang, J Eickholt, J Cheng Nucleic acids research 37 (suppl 2), W515-W518, 2009	198	2009
Predicting protein residue-residue contacts using deep networks and boosting J Eickholt, J Cheng Bioinformatics, 2012	184	2012
DeepSF: deep convolutional neural network for mapping protein sequences to folds J Hou, B Adhikari, J Cheng Bioinformatics 34 (8), 1295-1303, 2018	174	2018
CONFOLD: Residue‐residue contact‐guided ab initio protein folding B Adhikari, D Bhattacharya, R Cao, J Cheng Proteins: Structure, Function, and Bioinformatics 83 (8), 1436-1449, 2015	171	2015
Three-stage prediction of protein β-sheets by neural networks, alignments and graph algorithms J Cheng, P Baldi Bioinformatics 21 (suppl 1), i75-i84, 2005	167	2005
Large‐scale prediction of disulphide bridges using kernel methods, two‐dimensional recursive neural networks, and weighted graph matching J Cheng, H Saigo, P Baldi Proteins: Structure, Function, and Bioinformatics 62 (3), 617-629, 2006	162	2006
DeepQA: improving the estimation of single protein model quality with deep belief networks R Cao, D Bhattacharya, J Hou, J Cheng BMC Bioinformatics 17 (1), 495, 2016	161	2016

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